The resistance and short‐term resilience of a restored extracted peatland ecosystems post‐fire: an opportunistic study after a wildfire
Bibliographic record
Abstract
Bogs are known to be relatively resistant and resilient to fire, due to the dominance of wet Sphagnum mosses. Indeed, Sphagnum mosses by holding water, ensure bog resistance, and by regenerating from any fragments left post‐fire, ensure bog resilience. The return of several ecological attributes has been reported in the literature post‐restoration. However, the resistance and resilience have not yet been evaluated in restored peatlands. A fire affecting an extracted peatland restored 10 years ago provided the opportunity to (1) evaluate the losses post‐fire, in terms of phytobiomass and plant cover and (2) assess early vegetation recovery after one growing season post‐fire. The fire response of the restored peatland, in terms of resistance and short‐term resilience, differed between the main plant communities. Sphagnum Lawn communities ( Sphagnum species from the Acutifolia subgenus and Eriophorum vaginatum ) showed greater resistance to fire losing proportionally less phytobiomass (17%) than Wet Hollow communities (44%) ( Sphagnum species from the Cuspidata subgenus and Scirpus cyperinus ). Greater resistance of the Sphagnum Lawn likely comes from the Acutifolia Sphagnum species growing in dense carpets with good water retention, along with the E. vaginatum tussocks being able to retain humidity below the tussocks, whereas the looser growth habit of Cuspidata Sphagnum species do not have good capillary rise capacity and Scirpus produced litter that can produce a good fuel. This study reinforces the idea that a peatland restoration approach using reintroduction material dominated by Acutifolia Sphagnum species and tussock cottongrass provides a better resistance and short‐term resilience of restored peatlands.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".